TY - BOOK
T1 - Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
AU - Krainski, Elias
AU - Gómez-Rubio, Virgilio
AU - Bakka, Haakon
AU - Lenzi, Amanda
AU - Castro Camilo, Daniela
AU - Simpson, Daniel
AU - Lindgren, Finn
AU - Rue, Håvard
PY - 2018/12/31
Y1 - 2018/12/31
N2 - Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications.
AB - Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications.
U2 - 10.1201/9780429031892
DO - 10.1201/9780429031892
M3 - Book
SN - 9781138369856
BT - Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
PB - Taylor & Francis
CY - New York
ER -